NICE Actimize has added a trade reconstruction model to its surveillance portfolio. The solution uses machine learning analytics to classify and understand content based on previous examples and patented automated correlation capabilities to link trade executions to trade conversations. It can cut trade reconstruction time from days to minutes and is designed to support rapid trade reconstruction requirements of Markets in Financial Instruments Directive II (MiFID II), Market Abuse Regulation (MAR), Code of Conduct and Dodd-Frank regulations.
The solution simplifies the time-consuming and costly task of trade reconstruction by normalising, analysing, indexing and correlating data across all structured and unstructured data sources. By applying sophisticated analytics and correlation technology, it can determine which trade data and related communications are relevant for the trade reconstruction across all linked data sources. All trade reconstruction elements, including trade data, voice recordings and other electronic communications, can be retrieved in a single search, avoiding the need to navigate multiple systems.
Joe Friscia, president at NICE Actimize, says: “Under the weight of increasing regulatory pressures, financial services firms need a better way to reconstruct the lifecycle of a trade. NICE Actimize has used its experience in analytics, machine learning and data correlation to solve the problem by accurately automating the reconstruction of trades.”